Comprehensive and Integrative Genomic Characterization of Hepatocellular Carcinoma

Genetics of Hepatocellular Carcinoma: From Tumor to Circulating DNA

Hepatocellular carcinoma (HCC) accounts for 90% of primary hepatic malignancies and is one of the major causes of cancer-related death. Over the last 15 years, the molecular landscape of HCC has been deciphered, with the identification of the main driver genes of liver carcinogenesis that belong to six major biological pathways, such as telomere maintenance, Wnt/b-catenin, P53/cell cycle regulation, oxidative stress, epigenetic modifiers, AKT/mTOR and MAP kinase. The combination of genetic and transcriptomic data composed various HCC subclasses strongly related to risk factors, pathological features and prognosis. However, translation into clinical practice is not achieved, mainly because the most frequently mutated genes are undruggable. Moreover, the results derived from the analysis of a single tissue sample may not adequately catch the intra- and intertumor heterogeneity. The analysis of circulating tumor DNA (ctDNA) is broadly developed in other types of cancer for early diagnosis, prognosis and monitoring under systemic treatment in order to identify primary and secondary mechanisms of resistance. The aim of this review is to describe recent data about the HCC molecular landscape and to discuss how ctDNA could be used in the future for HCC detection and management.

Analysis of angiogenesis-related subtypes of hepatocellular carcinoma and tumor microenvironment infiltration feature in hepatocellular carcinoma

PURPOSE

Hepatocellular carcinoma (HCC) is a highly vascularized tumor, and angiogenesis plays an important role in its progression. However, the role of angiogenesis in cell infiltration in the tumor microenvironment (TME) remains unclear.

METHODS

We evaluated the associations of 35 angiogenesis-related genes (ARGs) with the clinicopathological features of 816 HCC patients. In addition, we assessed the associations between the ARGs and TME cell infiltration. A nomogram was constructed to determine the prognostic value of ARGs for HCC. The ARG score was used to distinguish angiogenic subtypes of HCC, and its usefulness for predicting the prognosis and treatment response of HCC patients was evaluated.

RESULTS

We distinguished three ARG clusters differing in terms of TME cell infiltration, immune cell activation status, clinicopathological features, and clinical outcomes. There were significant associations of ARG expression with tumor immunity, the epithelial-mesenchymal transition (EMT), and transforming growth factor-β expression. An ARG score model was constructed to generate a risk score for each patient based on differentially expressed genes between clusters. Furthermore, a high ARG score was associated with high expression of CTLA-4 and PD-L1/PD-1, and a low Tumor Immune Dysfunction and Exclusion score, indicating the usefulness of the ARG score for selecting patients for immunotherapy. Considering the relationship between ARGs and tumor immunity, immunotherapy combined with vascular-targeted therapy may be the best treatment for HCC.

CONCLUSIONS

ARGs play an important role in TME diversity and complexity in HCC patients. The ARG score of HCC predicts TME invasion and can guide immunotherapy.

Integrated investigation of the clinical implications and targeted landscape for RNA methylation modifications in hepatocellular carcinoma

BACKGROUND

RNA methylation (RM) is a crucial post-translational modification (PTM) that directs epigenetic regulation. It mostly consists of N¹-methyladenosine (m¹A), 5-methylcytosine (m⁵C), N³-methylcytidine (m³C), N⁶-methyladenosine (m⁶A), and 2'-O-methylation (Nm). The "writers" mainly act as intermediaries between these modifications and associated biological processes. However, little is known about the interactions and potential functions of these RM writers in hepatocellular carcinoma (HCC).

METHODS

The expression properties and genetic alterations of 38 RM writers were assessed in HCC samples from five bioinformatic datasets. Two patterns associated with RM writers were identified using consensus clustering. Then, utilizing differentially expressed genes (DEGs) from different RM subtypes, we built a risk model called RM_Score. Additionally, we investigated the correlation of RM_Score with clinical characteristics, tumor microenvironment (TME) infiltration, molecular subtypes, therapeutic response, immunotherapy effectiveness, and competing endogenous RNA (ceRNA) network.

RESULTS

RM writers were correlated with TME cell infiltration and prognosis. Cluster_1/2 and gene.cluster_A/B were shown to be capable of distinguishing the HCC patients with poor prognosis after consensus and unsupervised clustering of RNA methylation writers. Additionally, we constructed RNA modification pattern-specific risk model and subdivided the cases into RM_Score high and RM_Score low subgroups. In individual cohorts or merged datasets, the high RM_Score was related to a worse overall survival of HCC patients. RM_Score also exhibited correlations with immune and proliferation related pathways. In response to anti-cancer treatments, the RM_Score had a negative correlation (drug sensitive) with drugs that focused on the MAPK/ERK and metabolism signaling, and a positive correlation (drug resistant) with compounds targeting RKT and PI3K/mTOR signaling pathway. Notably, the RM_Score was connected to the therapeutic effectiveness of PD-L1 blockage, implying that RM writers may be the target of immunotherapy to optimize clinical outcomes. Additionally, a ceRNA network was generated including 2 lncRNAs, 4 miRNAs, and 7 mRNAs that was connected to RM writers.

CONCLUSIONS

We thoroughly investigated the potential functions of RNA methylation writers and established an RM_patterns-based risk model for HCC patients. This study emphasized the critical functions of RM modification in TME infiltration, targeted therapy, and immunotherapy, providing potential targets for HCC.

TRMT6 promotes hepatocellular carcinoma progression through the PI3K/AKT signaling pathway

BACKGROUND

Hepatocellular carcinoma is one of the most common and deadly cancers. The aim of this study was to elucidate the role of tRNA methyltransferase 6 (TRMT6) during HCC progression.

METHODS

The role of TRMT6 in the progression and prognosis of HCC was confirmed by analysis of online databases and clinical human samples. The effects of up-regulation or down-regulation of TRMT6 on HCC cell proliferation and PI3K/AKT pathway-related protein expressions were verified. The molecular mechanism was investigated in vivo by constructing subcutaneous xenograft tumor model.

RESULTS

TRMT6 was overexpressed in HCC tissues and associated with Tumour-Node-Metastasis (TNM) stage, primary tumor (T) and regional lymph node (N) classification. TRMT6 expressions in HCC cell lines were higher than that in normal liver cell. TRMT6 overexpression can promote HCC cell proliferation, increase the number of S phase cells. Interference with TRMT6 reduced the PI3K/AKT pathway-related protein expressions, and was reversed by the addition of IGF1. Interference with TRMT6 inhibited tumor growth in vivo and was related to PI3K/AKT pathway.

CONCLUSIONS

Overexpression of TRMT6 promote HCC cell proliferation in vivo and in vitro through PI3K/AKT/mTOR axis, which provides a potential choice for the treatment of HCC in clinical practice.

Oncogenic PKA signaling increases c-MYC protein expression through multiple targetable mechanisms

Genetic alterations that activate protein kinase A (PKA) are found in many tumor types. Yet, their downstream oncogenic signaling mechanisms are poorly understood. We used global phosphoproteomics and kinase activity profiling to map conserved signaling outputs driven by a range of genetic changes that activate PKA in human cancer. Two signaling networks were identified downstream of PKA: RAS/MAPK components and an Aurora Kinase A (AURKA)/glycogen synthase kinase (GSK3) sub-network with activity toward MYC oncoproteins. Findings were validated in two PKA-dependent cancer models: a novel, patient-derived fibrolamellar carcinoma (FLC) line that expresses a DNAJ-PKAc fusion and a PKA-addicted melanoma model with a mutant type I PKA regulatory subunit. We identify PKA signals that can influence both de novo translation and stability of the proto-oncogene c-MYC. However, the primary mechanism of PKA effects on MYC in our cell models was translation and could be blocked with the eIF4A inhibitor zotatifin. This compound dramatically reduced c-MYC expression and inhibited FLC cell line growth in vitro. Thus, targeting PKA effects on translation is a potential treatment strategy for FLC and other PKA-driven cancers.

Epigenetic dysregulation-mediated COL12A1 upregulation predicts worse outcome in intrahepatic cholangiocarcinoma patients

BACKGROUND

Collagen type XII alpha 1 chain (COL12A1) is associated with human cancer progression. Nevertheless, the expression pattern and the function of COL12A1 in intrahepatic cholangiocarcinoma (iCCA) remain unknown. The present study was performed to assess the role of COL12A1 in iCCA.

RESULTS

A total of 1669 genes, differentially expressed between iCCA and nontumor liver tissue samples, were identified as potential tumor-specific biomarkers for iCCA patients. Of these, COL12A1 was significantly upregulated in clinical iCCA tissue samples and correlated with epithelial-mesenchymal transition gene set enrichment score and advanced tumor stage in clinical iCCA. COL12A1-high expression was associated with the poor prognoses of iCCA patients (n = 421) from four independent cohorts. Promoter hypermethylation-induced downregulation of miR-424-5p resulted in COL12A1 upregulation in clinical iCCA. Experimental knockout of COL12A1 inhibited the proliferation, invasiveness and growth of iCCA cells. MiR-424-5p had a therapeutic potential in iCCA via directly targeting COL12A1.

CONCLUSIONS

Promoter hypermethylation-induced miR-424-5p downregulation contributes to COL12A1 upregulation in iCCA. COL12A1 is a promising druggable target for epigenetic therapy of iCCA.

Identifying key multifunctional components shared by critical cancer and normal liver pathways via SparseGMM

Despite the abundance of multimodal data, suitable statistical models that can improve our understanding of diseases with genetic underpinnings are challenging to develop. Here, we present SparseGMM, a statistical approach for gene regulatory network discovery. SparseGMM uses latent variable modeling with sparsity constraints to learn Gaussian mixtures from multiomic data. By combining coexpression patterns with a Bayesian framework, SparseGMM quantitatively measures confidence in regulators and uncertainty in target gene assignment by computing gene entropy. We apply SparseGMM to liver cancer and normal liver tissue data and evaluate discovered gene modules in an independent single-cell RNA sequencing (scRNA-seq) dataset. SparseGMM identifies PROCR as a regulator of angiogenesis and PDCD1LG2 and HNF4A as regulators of immune response and blood coagulation in cancer. Furthermore, we show that more genes have significantly higher entropy in cancer compared with normal liver. Among high-entropy genes are key multifunctional components shared by critical pathways, including p53 and estrogen signaling.

Advanced development of biomarkers for immunotherapy in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common liver cancer and one of the leading causes of cancer-related deaths in the world. Mono-immunotherapy and combination therapy with immune checkpoint inhibitors (ICIs) and multitargeted tyrosine kinase inhibitors (TKIs) or anti-vascular endothelial growth factor (anti-VEGF) inhibitors have become new standard therapies in advanced HCC (aHCC). However, the clinical benefit of these treatments is still limited. Thus, proper biomarkers which can predict treatment response to immunotherapy to maximize clinical benefit while sparing unnecessary toxicity are urgently needed. Contrary to other malignancies, up until now, no acknowledged biomarkers are available to predict resistance or response to immunotherapy for HCC patients. Furthermore, biomarkers, which are established in other cancer types, such as programmed death ligand 1 (PD-L1) expression and tumor mutational burden (TMB), have no stable predictive effect in HCC. Thus, plenty of research focusing on biomarkers for HCC is under exploration. In this review, we summarize the predictive and prognostic biomarkers as well as the potential predictive mechanism in order to guide future research direction for biomarker exploration and clinical treatment options in HCC.

The apolipoprotein B and apolipoprotein A-I Ratio serves as a strong prognostic factor for the overall survival of patients with colorectal cancer

Background

The lipid metabolism status of patients with colorectal cancer (CRC) has not been understood comprehensively. The present study investigated the characteristics of lipid metabolism parameters in CRC patients with or without metastases and identified the independent prognostic factors of long-term prognosis.

Methods

The clinicopathological data of 231 CRC patients along with 259 formalin-fixed paraffin-embedded samples with or without liver or lung metastasis were retrieved and stained for apolipoprotein B (apoB) via immunohistochemistry (IHC) in our center. The correlation and multivariable analysis between blood circulating apolipoprotein A-I (apoA1), apoB and overall survival (OS) were analyzed.

Results

In the multivariable analysis, apoA1, apoB and apolipoprotein B and apolipoprotein A-I (apoB/A) ratio, were identified as independent prognostic factors for OS. Moreover, the apoB/A ratio showed a significantly negative association with OS time (R=-0.187, P=0.004). CRC patients with low apoB/A ratio had better 1-, 3- and 5-year OS rates than those who had high apoB/A ratio (87.1%, 54.3%, and 37.1% vs. 92.5%, 72.0%, and 59.5%, respectively, P=0.001). On histological level, similar expression intensity of apoB between primary CRC and liver metastases indicated better prognostic outcomes than those with different expression levels (100%, 83.3%, and 77.8% vs. 100%, 66.7%, and 33.3%, respectively; P=0.033). Higher level of apoB in the primary CRC interprets into increased incidence of liver metastases. However, the apoB expression levels in the CRC tumor were not parallel to the circulating lipid metabolism parameters.

Conclusions

The apoB/A ratio was a reliable independent prognostic factor for predicting the long-term OS of CRC patients. Moreover, the IHC of the primary CRC and metastatic lesions verified the metastatic potential of apoB through a different aspect. Lipid metabolism status for cancer progression reported in the present study possessed potentially prognostic value, but bench-scale studies are needed for their future clinical applications.

Immunometabolic factors contributing to obesity-linked hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a major public health concern that is promoted by obesity and associated liver complications. Onset and progression of HCC in obesity is a multifactorial process involving complex interactions between the metabolic and immune system, in which chronic liver damage resulting from metabolic and inflammatory insults trigger carcinogenesis-promoting gene mutations and tumor metabolism. Moreover, cell growth and proliferation of the cancerous cell, after initiation, requires interactions between various immunological and metabolic pathways that provide stress defense of the cancer cell as well as strategic cell death escape mechanisms. The heterogenic nature of HCC in addition to the various metabolic risk factors underlying HCC development have led researchers to focus on examining metabolic pathways that may contribute to HCC development. In obesity-linked HCC, oncogene-induced modifications and metabolic pathways have been identified to support anabolic demands of the growing HCC cells and combat the concomitant cell stress, coinciding with altered utilization of signaling pathways and metabolic fuels involved in glucose metabolism, macromolecule synthesis, stress defense, and redox homeostasis. In this review, we discuss metabolic insults that can underlie the transition from steatosis to steatohepatitis and from steatohepatitis to HCC as well as aberrantly regulated immunometabolic pathways that enable cancer cells to survive and proliferate in the tumor microenvironment. We also discuss therapeutic modalities targeted at HCC prevention and regression. A full understanding of HCC-associated immunometabolic changes in obesity may contribute to clinical treatments that effectively target cancer metabolism.

PVRIG Expression Is an Independent Prognostic Factor and a New Potential Target for Immunotherapy in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a frequent and deadly cancer in need of new treatments. Immunotherapy has shown promising results in several solid tumors. The TIGIT/DNAM-1 axis gathers targets for new immune checkpoint inhibitors (ICIs). Here, we aimed at highlighting the potential of this axis as a new therapeutic option for HCC. For this, we built a large transcriptomic database of 683 HCC samples, clinically annotated, and 319 normal liver tissues. We interrogated this database for the transcriptomic expression of each member of the TIGIT/DNAM-1 axis and tested their prognostic value for survival. We then focused on the most discriminant one for these criteria, i.e., PVRIG, and analyzed the clinical characteristics, the disease-free and overall survivals, and biological pathways associated with PVRIG High tumors. Among all members of the TIGIT/DNAM-1 axis, PVRIG expression was higher in tumors than in normal liver, was heterogeneous across tumors, and was the only member with independent prognostic value for better survival. PVRIG High tumors were characterized by a higher lymphocytic infiltrate and enriched for signatures associated with tertiary lymphoid structures and better anti-tumor immune response. These results suggest that patients with PVRIG High tumors might be good candidates for immune therapy involving ICIs, notably ICIs targeting the TIGIT/DNAM-1 axis. Further functional and clinical validation is urgently required.

Current view of liver cancer cell-of-origin and proposed mechanisms precluding its proper determination

Hepatocellular carcinoma and intrahepatic cholangiocarcinoma are devastating primary liver cancers with increasing prevalence in many parts of the world. Despite intense investigation, many aspects of their biology are still largely obscure. For example, numerous studies have tackled the question of the cell-of-origin of primary liver cancers using different experimental approaches; they have not, however, provided a clear and undisputed answer. Here, we will review the evidence from animal models supporting the role of all major types of liver epithelial cells: hepatocytes, cholangiocytes, and their common progenitor as liver cancer cell-of-origin. Moreover, we will also propose mechanisms that promote liver cancer cell plasticity (dedifferentiation, transdifferentiation, and epithelial-to-mesenchymal transition) which may contribute to misinterpretation of the results and which make the issue of liver cancer cell-of-origin particularly complex.

Exploration of the potential mechanism of Baicalin for hepatic fibrosis based on network pharmacology, gut microbiota, and experimental validation

Baicalin (BA) is among the most effective and abundant flavonoids extracted from Scutellaria baicalensis that may be utilized to treat diseases associated with hepatic fibrosis (HF). Through network pharmacology, gut microbiota, and experimental validation, this research intends to elucidate the multi-target mechanism of BA on HF. BA targets were screened using databases and literature. As a result, In the anti-HF mechanism, the BA and 191 HF-associated targets interact, with 9 specific targets indicating that the BA's anti-HF mechanism is closely linked to gut microbiota. Consequently, rat intestinal content samples were obtained and examined using 16S rRNA sequencing. In the BA-treated group, the gut microbiota was positively regulated at the phylum,and genus levels, with Lactobacillus performing significantly. The study concluded that BA has a multi-targeted anti-HF effect and has changed the gut microbial ecosystem.

Molecular characterization of an embryonal rhabdomyosarcoma occurring in a patient with Kabuki syndrome: report and literature review in the light of tumor predisposition syndromes

Kabuki syndrome is a well-recognized syndrome characterized by facial dysmorphism and developmental delay/intellectual disability and in the majority of patients a germline variant in KMT2D is found. As somatic KMT2D variants can be found in 5-10% of tumors a tumor predisposition in Kabuki syndrome is discussed. So far less than 20 patients with Kabuki syndrome and a concomitant malignancy have been published. Here we report on a female patient with Kabuki syndrome and a c.2558_2559delCT germline variant in KMT2D who developed an embryonal rhabdomyosarcoma (ERMS) at 10 years. On tumor tissue we performed DNA-methylation profiling and exome sequencing (ES). Copy number analyses revealed aneuploidies typical for ERMS including (partial) gains of chromosomes 2, 3, 7, 8, 12, 15, and 20 and 3 focal deletions of chromosome 11p. DNA methylation profiling mapped the case to ERMS by a DNA methylation-based sarcoma classifier. Sequencing suggested gain of the wild-type KMT2D allele in the trisomy 12. Including our patient literature review identified 18 patients with Kabuki syndrome and a malignancy. Overall, the landscape of malignancies in patients with Kabuki syndrome was reminiscent of that of the pediatric population in general. Histopathological and molecular data were only infrequently reported and no report included next generation sequencing and/or DNA-methylation profiling. Although we found no strong arguments pointing towards KS as a tumor predisposition syndrome, based on the small numbers any relation cannot be fully excluded. Further planned studies including profiling of additional tumors and long term follow-up of KS-patients into adulthood could provide further insights.

Immune index: A gene and cell prognostic signature for immunotherapy response prediction in hepatocellular carcinoma

The heterogeneity of tumor immune microenvironment (TIME) plays important roles in the development and immunotherapy response of hepatocellular carcinoma (HCC). Using machine learning algorithms, we introduced the immune index (IMI), a prognostic model based on the HCC immune landscape. We found that IMI low HCCs were enriched in stem cell and proliferating signatures, and yielded more TP53 mutation and 17p loss compared with IMI high HCCs. More importantly, patients with high IMI exhibited better immune-checkpoint blockade (ICB) response. To facilitate clinical application, we employed machine learning algorithms to develop a gene model of the IMI (IMI_G), which contained 10 genes. According to our HCC cohort examination and single-cell level analysis, we found that IMI_G high HCCs exhibited favorable survival outcomes and high levels of NK and CD8⁺ T cells infiltration. Finally, after coculture with autologous tumor infiltrating lymphocytes, IMI_G high tumor cells exhibited a better response to nivolumab treatment. Collectively, the IMI and IMI_G may serve as powerful tools for the prognosis, classification and ICB treatment response prediction of HCC.

DNA methylation in cell plasticity and malignant transformation in liver diseases

The liver possesses extraordinary regenerative capacity mainly attributable to the ability of hepatocytes (HCs) and biliary epithelial cells (BECs) to self-replicate. This ability is left over from their bipotent parent cell, the hepatoblast, during development. When this innate regeneration is compromised due to the absence of proliferative parenchymal cells, such as during cirrhosis, HCs and BEC can transdifferentiate; thus, adding another layer of complexity to the process of liver repair. In addition, dysregulated lineage maintenance in these two cell populations has been shown to promote malignant growth in experimental conditions. Here, malignant transformation, driven in part by insufficient maintenance of lineage reprogramming, contributes to end-stage liver disease. Epigenetic changes are key drivers for cell fate decisions as well as transformation by finetuning overall transcription and gene expression. In this review, we address how altered DNA methylation contributes to the initiation and progression of hepatic cell fate conversion and cancer formation. We also discussed the diagnostic and therapeutic potential of targeting DNA methylation in liver cancer, its current limitations, and what future research is necessary to facilitate its contribution to clinical translation.

Proteomics profiling of nontumor liver tissues identifies prognostic biomarkers in hepatitis B-related hepatocellular carcinoma

Hepatocellular carcinoma (HCC) often occurs following chronic hepatitis B virus (HBV) infection, leading to high recurrence and a low 5-year survival rate. We developed an overall survival (OS) prediction model based on protein expression profiles in HBV-infected nontumor liver tissues. We aimed to demonstrate the feasibility of using protein expression profiles in nontumor liver tissues for survival prediction. A univariate Cox and differential expression analysis were performed to identify candidate prognostic factors. A multivariate Cox analysis was performed to develop the liver gene prognostic index (LGPI). The survival differences between the different risk groups in the training and validation cohorts were also estimated. A total of 363 patients, 159 in the training cohort, and 204 in the validation cohort were included. Of the 6478 proteins extracted from nontumor liver tissues, we identified 1275 proteins altered between HCC and nontumor liver tissues. A total of 1090 out of 6478 proteins were significantly related to OS. The prognostic values of the proteins in nontumor tissues were mostly positively related to those in the tumor tissues. Protective proteins were mainly enriched in the metabolism-related pathways. From the differentially expressed proteins, the top 10 most significant prognosis-related proteins were submitted for LGPI construction. In the training and validation cohorts, this LGPI showed a great ability for distinguishing patients' OS risk stratifications. After adjusting for clinicopathological features, the LGPI was an independent prognostic factor in the training and validation cohorts. We demonstrated the prognostic value of protein expression profiling in nontumor liver tissues. The proposed LGPI was a promising predictive model for estimating OS in HBV-related HCC.

Molecular and radiopathologic spectrum between HCC and intrahepatic cholangiocarcinoma

BACKGROUND AND AIMS

Primary liver cancers (LCs), including HCC and intrahepatic cholangiocarcinoma (iCCA), are derived from a common developmental lineage, conferring a molecular spectrum between them. To elucidate the molecular spectrum, we performed an integrative analysis of transcriptome profiles associated with patients' radiopathologic features.

APPROACH AND RESULTS

We identified four LC subtypes (LC1-LC4) from RNA-sequencing profiles, revealing intermediate subtypes between HCC and iCCA. LC1 is a typical HCC characterized by active bile acid metabolism, telomerase reverse transcriptase promoter mutations, and high uptake of gadoxetic acid in MRI. LC2 is an iCCA-like HCC characterized by expression of the progenitor cell-like trait, tumor protein p53 mutations, and rim arterial-phase hyperenhancement in MRI. LC3 is an HCC-like iCCA, mainly small duct (SD) type, associated with HCC-related etiologic factors. LC4 is further subclassified into LC4-SD and LC4-large duct iCCAs according to the pathological features, which exhibited distinct genetic variations (e.g., KRAS , isocitrate dehydrogenase 1/2 mutation, and FGF receptor 2 fusion), stromal type, and prognostic outcomes.

CONCLUSIONS

Our integrated view of the molecular spectrum of LCs can identify subtypes associated with transcriptomic, genomic, and radiopathologic features, providing mechanistic insights into heterogeneous LC progression.

A novel zinc metabolism-related gene signature to predict prognosis and immunotherapy response in lung adenocarcinoma

Background

Zinc is a key mineral element in regulating cell growth, development, and immune system. We constructed the zinc metabolism-related gene signature to predict prognosis and immunotherapy response for lung adenocarcinoma (LUAD).

Methods

Zinc metabolism-associated gene sets were obtained from Molecular Signature Database. Then, the zinc metabolism-related gene signature (ZMRGS) was constructed and validated. After combining with clinical characteristics, the nomogram for practical application was constructed. The differences in biological pathways, immune molecules, and tumor microenvironment (TME) between the different groups were analyzed. Tumor Immune Dysfunction and Exclusion algorithm (TIDE) and two immunotherapy datasets were used to evaluate the immunotherapy response.

Results

The signature was constructed according to six key zinc metabolism-related genes, which can well predict the prognosis of LUAD patients. The nomogram also showed excellent prediction performance. Functional analysis showed that the low-risk group was in the status of immune activation. More importantly, the lower risk score of LUAD patients showed a higher response rate to immunotherapy.

Conclusion

The state of zinc metabolism is closely connected to prognosis, tumor microenvironment, and response to immunotherapy. The zinc metabolism-related signature can well evaluate the prognosis and immunotherapy response for LUAD patients.

Statistical Methods for Integrative Clustering of Multi-omics Data

Cancers are heterogeneous diseases caused by accumulated mutations or abnormal alterations at multi-levels of biological processes including genomics, epigenomics, transcriptomics, and proteomics. There is a great clinical interest in identifying cancer molecular subtypes for disease prognosis and personalized medicine. Integrative clustering is a powerful unsupervised learning method that has been increasingly used to identify cancer molecular subtypes using multi-omics data including somatic mutations, DNA copy numbers, DNA methylation, and gene expression. Integrative clustering methods are generally classified into model-based or nonparametric approaches. In this chapter, we will give an overview of the frequently used model-based methods, including iCluster, iClusterPlus, and iClusterBayes, and the nonparametric method, integrative nonnegative matrix factorization (intNMF). We will use the integrative analyses of uveal melanoma and lower-grade glioma to illustrate these representative methods. Finally, we will discuss the strengths and limitations of these representative methods and give suggestions for performing integrative analyses of cancer multi-omics data in practice.

Multiomics identifies the link between intratumor steatosis and the exhausted tumor immune microenvironment in hepatocellular carcinoma

BACKGROUND AND AIMS

Immunotherapy has become the standard-of-care treatment for hepatocellular carcinoma (HCC), but its efficacy remains limited. To identify immunotherapy-susceptible HCC, we profiled the molecular abnormalities and tumor immune microenvironment (TIME) of rapidly increasing nonviral HCC.

APPROACHES AND RESULTS

We performed RNA-seq of tumor tissues in 113 patients with nonviral HCC and cancer genome sequencing of 69 genes with recurrent genetic alterations reported in HCC. Unsupervised hierarchical clustering classified nonviral HCCs into three molecular classes (Class I, II, III), which stratified patient prognosis. Class I, with the poorest prognosis, was associated with TP53 mutations, whereas class III, with the best prognosis, was associated with cadherin-associated protein beta 1 (CTNNB1) mutations. Thirty-eight percent of nonviral HCC was defined as an immune class characterized by a high frequency of intratumoral steatosis and a low frequency of CTNNB1 mutations. Steatotic HCC, which accounts for 23% of nonviral HCC cases, presented an immune-enriched but immune-exhausted TIME characterized by T cell exhaustion, M2 macrophage and cancer-associated fibroblast (CAF) infiltration, high PD-L1 expression, and TGF-β signaling activation. Spatial transcriptome analysis suggested that M2 macrophages and CAFs may be in close proximity to exhausted CD8+ T cells in steatotic HCC. An in vitro study showed that palmitic acid-induced lipid accumulation in HCC cells upregulated PD-L1 expression and promoted immunosuppressive phenotypes of cocultured macrophages and fibroblasts. Patients with steatotic HCC, confirmed by chemical-shift MR imaging, had significantly longer PFS with combined immunotherapy using anti-PD-L1 and anti-VEGF antibodies.

CONCLUSIONS

Multiomics stratified nonviral HCCs according to prognosis or TIME. We identified the link between intratumoral steatosis and immune-exhausted immunotherapy-susceptible TIME.

Multiview Robust Graph-Based Clustering for Cancer Subtype Identification

Cancer subtype identification is to classify cancer into groups according to their molecular characteristics and clinical manifestations and is the basis for more personalized diagnosis and therapy. Public datasets such as The Cancer Genome Atlas (TCGA) have collected a massive number of multi-omics data. The accumulation of these datasets provides unprecedented opportunities to study the mechanism of cancers and further identify cancer subtypes at a comprehensive level. In this paper, we propose a multi-view robust graph-based clustering (MRGC) method to effectively identify cancer subtypes. Our method first learns robust latent representations from the raw omics data to alleviate the influences of the noise, where a set of similarity matrices are then adaptively learned based on these new representations. Finally, a global similarity graph is obtained by exploiting the consensus structure from the graphs. As a result, the three parts in our method can reinforce each other in a mutual iterative manner. We conduct extensive experiments on both generic machine learning datasets and cancer datasets. The experimental results confirm that our model can achieve satisfactory clustering performance compared to several state-of-the-art approaches. Moreover, we convey the practicability of MRGC by carrying out a case study on hepatocellular carcinoma.

Splice-switch oligonucleotide-based combinatorial platform prioritizes synthetic lethal targets CHK1 and BRD4 against MYC-driven hepatocellular carcinoma

Deregulation of MYC is among the most frequent oncogenic drivers in hepatocellular carcinoma (HCC). Unfortunately, the clinical success of MYC-targeted therapies is limited. Synthetic lethality offers an alternative therapeutic strategy by leveraging on vulnerabilities in tumors with MYC deregulation. While several synthetic lethal targets of MYC have been identified in HCC, the need to prioritize targets with the greatest therapeutic potential has been unmet. Here, we demonstrate that by pairing splice-switch oligonucleotide (SSO) technologies with our phenotypic-analytical hybrid multidrug interrogation platform, quadratic phenotypic optimization platform (QPOP), we can disrupt the functional expression of these targets in specific combinatorial tests to rapidly determine target-target interactions and rank synthetic lethality targets. Our SSO-QPOP analyses revealed that simultaneous attenuation of CHK1 and BRD4 function is an effective combination specific in MYC-deregulated HCC, successfully suppressing HCC progression in vitro. Pharmacological inhibitors of CHK1 and BRD4 further demonstrated its translational value by exhibiting synergistic interactions in patient-derived xenograft organoid models of HCC harboring high levels of MYC deregulation. Collectively, our work demonstrates the capacity of SSO-QPOP as a target prioritization tool in the drug development pipeline, as well as the therapeutic potential of CHK1 and BRD4 in MYC-driven HCC.

Integrated analysis of transcriptomics and metabolomics in human hepatocellular carcinoma HepG2215 cells after YAP1 knockdown

Yes-associated protein 1 (YAP1) plays a critical role in hepatocellular carcinoma (HCC). Inhibition of YAP1 expression suppresses HCC progression, but the underlying mechanism is still unclear. In this study, we studied the effects and molecular mechanisms of YAP1 knockdown on the growth and metabolism in human HCC HepG2215 cells. Inhibition of YAP1 expression inhibits the proliferation and metastasis in HepG2215 cells, and differentially expressed genes (DEGs) and metabolites were identified in shYAP1-HepG2215 cells. Further, 805 DEGs, mainly associated with metabolism and particularly lipid metabolism, were identified by transcriptome sequencing analyses in shYAP1-HepG2215 cells. YAP1 knockdown increased albumin (ALB) levels by Protein-protein interaction (PPI) network analyses in HepG2215 cells. Metabolomic profiling identified 37 metabolites with significant differences in the shYAP1 group, and amino acid metabolism generally decreased in the shYAP1 group. Comprehensive analysis of transcriptomics and metabolomics revealed that the ATP-binding cassette (ABC) transporters play a central role after YAP1 knockdown in HepG2215 cells. Therefore, YAP1 knockdown inhibited HCC growth, which affected the metabolism of lipids and amino acids by regulating the expression of ALB and ABC transporters in HepG2215 cells.

Hepatic Sarcomatoid Carcinoma Is an Aggressive Hepatic Neoplasm Sharing Common Molecular Features With Its Conventional Carcinomatous Counterparts

Hepatic sarcomatoid carcinoma is a rare hepatic tumor with an aggressive clinical behavior and dismal outcome. However, the molecular pathogenesis is incompletely defined. In this study, we analyzed 59 hepatic sarcomatoid carcinomas using targeted next-generation sequencing and immunohistochemistry. A panel of 14 genes commonly mutated in primary liver carcinomas was examined. PD-L1 and loss of expression for switch/sucrose nonfermenting complexes, including BAP1, ARID1A, ARID2, and PBRM1, were detected by immunohistochemistry. The 59 hepatic sarcomatoid carcinomas encompass various carcinomatous subtypes and tumors with complete sarcomatoid transformation. Mutations in TP53 and promoter of TERT (pTERT) were frequently identified in sarcomatoid hepatocellular carcinoma, sarcomatoid combined hepatocellular cholangiocarcinoma, and hepatic sarcomatoid carcinomas with complete sarcomatoid transformation but rarely in sarcomatoid cholangiocarcinoma. Alterations involving switch/sucrose nonfermenting complexes were uncommon in hepatic sarcomatoid carcinoma (n = 2). PD-L1 expressed in tumor-associated immune cells in 67% of the tumors and in tumor cells in 33% of the tumors. A multivariate survival analysis indicated that PD-L1 expression in immune cells served as an independent favorable predictive factor of patient survival (P = .036). In conclusion, hepatic sarcomatoid carcinoma displays molecular similarity with its conventional carcinomatous counterparts. This finding suggests persistent genetic characteristics during sarcomatous evolution. PD-L1 expression in immune cells is a favorable prognostic factor for patient outcomes and may be a potential biomarker for immunotherapeutic treatment.

SP70 is a novel biomarker of hepatocellular carcinoma

Background

Tumor-specific protein 70 (SP70) was identified as a new biomarker associated with the proliferation and invasion of cancer cells. This study aimed to investigate the expression of SP70 in hepatocellular carcinoma (HCC) and assess its clinical value in the diagnosis and prediction of early HCC recurrence.

Methods

A total of 1049 subjects from the First Affiliated Hospital of Nanjing Medical University were recruited in this study. Serum SP70, alpha-fetoprotein (AFP) and prothrombin induced by vitamin K absence II (PIVKA-II) were measured. The diagnostic performance for HCC was obtained using the receiver operating characteristic (ROC) curve, and recurrence-free survival (RFS) was calculated using the Kaplan-Meier method. Univariate and multivariate analyses were performed to identify predictive factors of RFS.

Results

SP70 was highly expressed in HCC cells and HCC tissue. Serum SP70 levels in the HCC group were significantly higher than in the benign liver diseases group and healthy control group (P<0.001). SP70 combined with AFP showed the best diagnostic performance (AUC=0.909, 95%CI [confidence interval]=0.890-0.929). Kaplan-Meier analysis revealed that patients with high SP70 levels had shorter median RFS than those with low SP70 levels (P=0.003). In addition, high SP70 levels were significantly associated with shorter RFS (P=0.037) in the AFP-negative subgroup. Univariate and multivariate analyses confirmed that preoperative serum SP70 level, serum AFP, tumor diameter and microvascular invasion were independent prognostic factors of RFS.

Conclusion

SP70 is a promising biomarker in diagnosing HCC. High preoperative serum SP70 level is associated with an increased risk of early relapse and could be used as a valuable marker to predict early recurrence of HCC after resection.

Inflamed and non-inflamed classes of HCC: a revised immunogenomic classification

OBJECTIVE

We previously reported a characterisation of the hepatocellular carcinoma (HCC) immune contexture and described an immune-specific class. We now aim to further delineate the immunogenomic classification of HCC to incorporate features that explain responses/resistance to immunotherapy.

DESIGN

We performed RNA and whole-exome sequencing, T-cell receptor (TCR)-sequencing, multiplex immunofluorescence and immunohistochemistry in a novel cohort of 240 HCC patients and validated our results in other cohorts comprising 660 patients.

RESULTS

Our integrative analysis led to define: (1) the inflamed class of HCC (37%), which includes the previously reported immune subclass (22%) and a new immune-like subclass (15%) with high interferon signalling, cytolytic activity, expression of immune-effector cytokines and a more diverse T-cell repertoire. A 20-gene signature was able to capture ~90% of these tumours and is associated with response to immunotherapy. Proteins identified in liquid biopsies recapitulated the inflamed class with an area under the ROC curve (AUC) of 0.91; (2) The intermediate class, enriched in TP53 mutations (49% vs 29%, p=0.035), and chromosomal losses involving immune-related genes and; (3) the excluded class, enriched in CTNNB1 mutations (93% vs 27%, p<0.001) and PTK2 overexpression due to gene amplification and promoter hypomethylation. CTNNB1 mutations outside the excluded class led to weak activation of the Wnt-βcatenin pathway or occurred in HCCs dominated by high interferon signalling and type I antigen presenting genes.

CONCLUSION

We have characterised the immunogenomic contexture of HCC and defined inflamed and non-inflamed tumours. Two distinct CTNNB1 patterns associated with a differential role in immune evasion are described. These features may help predict immune response in HCC.

Single-cell RNA analysis to identify five cytokines signaling in immune-related genes for melanoma survival prognosis

Melanoma is one of the deadliest skin cancers. Recently, developed single-cell sequencing has revealed fresh insights into melanoma. Cytokine signaling in the immune system is crucial for tumor development in melanoma. To evaluate melanoma patient diagnosis and treatment, the prediction value of cytokine signaling in immune-related genes (CSIRGs) is needed. In this study, the machine learning method of least absolute selection and shrinkage operator (LASSO) regression was used to establish a CSIRG prognostic signature of melanoma at the single-cell level. We discovered a 5-CSIRG signature that was substantially related to the overall survival of melanoma patients. We also constructed a nomogram that combined CSIRGs and clinical features. Overall survival of melanoma patients can be consistently predicted with good performance as well as accuracy by both the 5-CSIRG signature and nomograms. We compared the melanoma patients in the CSIRG high- and low-risk groups in terms of tumor mutation burden, infiltration of the immune system, and gene enrichment. High CSIRG-risk patients had a lower tumor mutational burden than low CSIRG-risk patients. The CSIRG high-risk patients had a higher infiltration of monocytes. Signaling pathways including oxidative phosphorylation, DNA replication, and aminoacyl tRNA biosynthesis were enriched in the high-risk group. For the first time, we constructed and validated a machine-learning model by single-cell RNA-sequencing datasets that have the potential to be a novel treatment target and might serve as a prognostic biomarker panel for melanoma. The 5-CSIRG signature may assist in predicting melanoma patient prognosis, biological characteristics, and appropriate therapy.

The Clinical Relevance and Immune Correlation of SLC10 Family Genes in Liver Cancer

Background and Aim

This study was aimed to reveal the clinical relevance and immune correlation of the SLC10 family genes in liver cancer.

Methods

A comprehensive bioinformatics analysis was utilized to determine the gene expression, genetic alterations, DNA methylation, clinical significance, survival association and immune correlation of seven SLC10 family genes in liver cancer. The multiplexed immunohistochemical technique was applied to determine the association between SLC10A3 protein expression and immune cells, and the correlation between SLC10A3 protein and immune checkpoints (PD1 and PD-L1) in a cohort of 32 individuals with liver cancer.

Results

The expression of SLC10 family genes was different between normal liver tissues and malignant liver tissues. SLC10A5 showed the highest alteration rate (8%), followed by SLC10A3 (2.8%). Low expression of SLC10A1 was indicative of poor tumor grade and advanced tumor stage in liver cancer. Scatter plots uncovered that expression of SLC10A3 was inversely associated with SLC10A1 and SLC10A5 expression in liver cancer. The expression of SLC10A1 and SLC10A5 was strongly associated with their DNA methylation. SLC10A1 expression was a reliable genetic biomarker for the prediction of survival outcomes in liver cancer population. Expression of SLC10 family genes was remarkably linked with the abundance of most immune infiltrating cells in liver cancer, and SLC10A3 was the most significant member. The multiplexed immunohistochemical technique confirmed that there existed the significant correlations between SLC10A3 protein expression and CD4 T cells, CD20 B cells and the close association with PD-1 in the stromal area from malignant tissues.

Conclusion

The expressions of SLC10 family genes were different between normal liver tissues and malignant liver tissues, and they were correlated with each other in liver cancer. SLC10A1 possesses the most significant correlation with survival outcomes. SLC10A3 exhibited the most significant relationship with immune cells, as revealed by bioinformatics analysis and multispectral imaging technique.

Deciphering Tumour Microenvironment of Liver Cancer through Deconvolution of Bulk RNA-Seq Data with Single-Cell Atlas

Liver cancers give rise to a heavy burden on healthcare worldwide. Understanding the tumour microenvironment (TME) underpins the development of precision therapy. Single-cell RNA sequencing (scRNA-seq) technology has generated high-quality cell atlases of the TME, but its wider application faces enormous costs for various clinical circumstances. Fortunately, a variety of deconvolution algorithms can instead repurpose bulk RNA-seq data, alleviating the need for generating scRNA-seq datasets. In this study, we reviewed major public omics databases for relevance in this study and utilised eight RNA-seqs and one microarray dataset from clinical studies. To decipher the TME of liver cancer, we estimated the fractions of liver cell components by deconvoluting the samples with Cibersortx using three reference scRNA-seq atlases. We also confirmed that Cibersortx can accurately deconvolute cell types/subtypes of interest. Compared with non-tumorous liver, liver cancers showed multiple decreased cell types forming normal liver microarchitecture, as well as elevated cell types involved in fibrogenesis, abnormal angiogenesis, and disturbed immune responses. Survival analysis shows that the fractions of five cell types/subtypes significantly correlated with patient outcomes, indicating potential therapeutic targets. Therefore, deconvolution of bulk RNA-seq data with scRNA-seq atlas references can be a useful tool to help understand the TME.

Identification of hepatocellular carcinoma subtypes based on PcG-related genes and biological relevance with cancer cells

BACKGROUND

Hepatocellular carcinoma (HCC) is an extensive heterogeneous disease where epigenetic factors contribute to its pathogenesis. Polycomb group (PcG) proteins are a group of subunits constituting various macro-molecular machines to regulate the epigenetic landscape, which contributes to cancer phenotype and has the potential to develop a molecular classification of HCC.

RESULTS

Here, based on multi-omics data analysis of DNA methylation, mRNA expression, and copy number of PcG-related genes, we established an epigenetic classification system of HCC, which divides the HCC patients into two subgroups with significantly different outcomes. Comparing these two epigenetic subgroups, we identified different metabolic features, which were related to epigenetic regulation of polycomb-repressive complex 1/2 (PRC1/2). Furthermore, we experimentally proved that inhibition of PcG complexes enhanced the lipid metabolism and reduced the capacity of HCC cells against glucose shortage. In addition, we validated the low chemotherapy sensitivity of HCC in Group A and found inhibition of PRC1/2 promoted HCC cells' sensitivity to oxaliplatin in vitro and in vivo. Finally, we found that aberrant upregulation of CBX2 in Group A and upregulation of CBX2 were associated with poor prognosis in HCC patients. Furthermore, we found that manipulation of CBX2 affected the levels of H3K27me3 and H2AK119ub.

CONTRIBUTIONS

Our study provided a novel molecular classification system based on PcG-related genes data and experimentally validated the biological features of HCC in two subgroups. Our founding supported the polycomb complex targeting strategy to inhibit HCC progression where CBX2 could be a feasible therapeutic target.

ACTR5 controls CDKN2A and tumor progression in an INO80-independent manner

Epigenetic dysregulation of cell cycle is a hallmark of tumorigenesis in multiple cancers, including hepatocellular carcinoma (HCC). Nonetheless, the epigenetic mechanisms underlying the aberrant cell cycle signaling and therapeutic response remain unclear. Here, we used an epigenetics-focused CRISPR interference screen and identified ACTR5 (actin-related protein 5), a component of the INO80 chromatin remodeling complex, to be essential for HCC tumor progression. Suppression of ACTR5 activated CDKN2A expression, ablated CDK/E2F-driven cell cycle signaling, and attenuated HCC tumor growth. Furthermore, high-density CRISPR gene tiling scans revealed a distinct HCC-specific usage of ACTR5 and its interacting partner IES6 compared to the other INO80 complex members, suggesting an INO80-independent mechanism of ACTR5/IES6 in supporting the HCC proliferation. Last, our study revealed the synergism between ACTR5/IES6-targeting and pharmacological inhibition of CDK in treating HCC. These results indicate that the dynamic interplay between epigenetic regulators, tumor suppressors, and cell cycle machinery could provide novel opportunities for combinational HCC therapy.

Multi-region sequencing with spatial information enables accurate heterogeneity estimation and risk stratification in liver cancer

BACKGROUND

Numerous studies have used multi-region sampling approaches to characterize intra-tumor heterogeneity (ITH) in hepatocellular carcinoma (HCC). However, conventional multi-region sampling strategies do not preserve the spatial details of samples, and thus, the potential influences of spatial distribution on patient-wise ITH (represents the overall heterogeneity level of the tumor in a given patient) have long been overlooked. Furthermore, gene-wise transcriptional ITH (represents the expression pattern of genes across different intra-tumor regions) in HCC is also under-explored, highlighting the need for a comprehensive investigation.

METHODS

To address the problem of spatial information loss, we propose a simple and easy-to-implement strategy called spatial localization sampling (SLS). We performed multi-region sampling and sequencing on 14 patients with HCC, collecting a total of 75 tumor samples with spatial information and molecular data. Normalized diversity score and integrated heterogeneity score (IHS) were then developed to measure patient-wise and gene-wise ITH, respectively.

RESULTS

A significant correlation between spatial and molecular heterogeneity was uncovered, implying that spatial distribution of sampling sites did influence ITH estimation in HCC. We demonstrated that the normalized diversity score had the ability to overcome sampling location bias and provide a more accurate estimation of patient-wise ITH. According to this metric, HCC tumors could be divided into two classes (low-ITH and high-ITH tumors) with significant differences in multiple biological properties. Through IHS analysis, we revealed a highly heterogenous immune microenvironment in HCC and identified some low-ITH checkpoint genes with immunotherapeutic potential. We also constructed a low-heterogeneity risk stratification (LHRS) signature based on the IHS results which could accurately predict the survival outcome of patients with HCC on a single tumor biopsy sample.

CONCLUSIONS

This study provides new insights into the complex phenotypes of HCC and may serve as a guide for future studies in this field.

Glutamine synthetase limits β-catenin-mutated liver cancer growth by maintaining nitrogen homeostasis and suppressing mTORC1

Glutamine synthetase (GS) catalyzes de novo synthesis of glutamine that facilitates cancer cell growth. In the liver, GS functions next to the urea cycle to remove ammonia waste. As a dysregulated urea cycle is implicated in cancer development, the impact of GS's ammonia clearance function has not been explored in cancer. Here, we show that oncogenic activation of β-catenin (encoded by CTNNB1) led to a decreased urea cycle and elevated ammonia waste burden. While β-catenin induced the expression of GS, which is thought to be cancer promoting, surprisingly, genetic ablation of hepatic GS accelerated the onset of liver tumors in several mouse models that involved β-catenin activation. Mechanistically, GS ablation exacerbated hyperammonemia and facilitated the production of glutamate-derived nonessential amino acids, which subsequently stimulated mechanistic target of rapamycin complex 1 (mTORC1). Pharmacological and genetic inhibition of mTORC1 and glutamic transaminases suppressed tumorigenesis facilitated by GS ablation. While patients with hepatocellular carcinoma, especially those with CTNNB1 mutations, have an overall defective urea cycle and increased expression of GS, there exists a subset of patients with low GS expression that is associated with mTORC1 hyperactivation. Therefore, GS-mediated ammonia clearance serves as a tumor-suppressing mechanism in livers that harbor β-catenin activation mutations and a compromised urea cycle.

Genome-scale CRISPR screening in a single mouse liver

A complete understanding of the genetic determinants underlying mammalian physiology and disease is limited by the capacity for high-throughput genetic dissection in the living organism. Genome-wide CRISPR screening is a powerful method for uncovering the genetic regulation of cellular processes, but the need to stably deliver single guide RNAs to millions of cells has largely restricted its implementation to ex vivo systems. There thus remains a need for accessible high-throughput functional genomics in vivo. Here, we establish genome-wide screening in the liver of a single mouse and use this approach to uncover regulation of hepatocyte fitness. We uncover pathways not identified in cell culture screens, underscoring the power of genetic dissection in the organism. The approach we developed is accessible, scalable, and adaptable to diverse phenotypes and applications. We have hereby established a foundation for high-throughput functional genomics in a living mammal, enabling comprehensive investigation of physiology and disease.

Recent progress in molecular mechanisms of postoperative recurrence and metastasis of hepatocellular carcinoma

Hepatectomy is currently considered the most effective option for treating patients with early and intermediate hepatocellular carcinoma (HCC). Unfortunately, the postoperative prognosis of patients with HCC remains unsatisfactory, predominantly because of high postoperative metastasis and recurrence rates. Therefore, research on the molecular mechanisms of postoperative HCC metastasis and recurrence will help develop effective intervention measures to prevent or delay HCC metastasis and recurrence and to improve the long-term survival of HCC patients. Herein, we review the latest research progress on the molecular mechanisms underlying postoperative HCC metastasis and recurrence to lay a foundation for improving the understanding of HCC metastasis and recurrence and for developing more precise prevention and intervention strategies.

Exosomal long non-coding RNAs: novel molecules in gastrointestinal cancers' progression and diagnosis

Gastrointestinal (GI) cancers arise in the GI tract and accessory organs, including the mouth, esophagus, stomach, liver, biliary tract, pancreas, small intestine, large intestine, and rectum. GI cancers are a major cause of cancer-related morbidity and mortality worldwide. Exosomes act as mediators of cell-to-cell communication, with pleiotropic activity in the regulation of homeostasis, and can be markers for diseases. Non-coding RNAs (ncRNAs), such as long non-coding RNAs (lncRNAs), can be transported by exosomes derived from tumor cells or non-tumor cells. They can be taken by recipient cells to alter their function or remodel the tumor microenvironment. Moreover, due to their uniquely low immunogenicity and excellent stability, exosomes can be used as natural carriers for therapeutic ncRNAs in vivo. Exosomal lncRNAs have a crucial role in regulating several cancer processes, including angiogenesis, proliferation, drug resistance, metastasis, and immunomodulation. Exosomal lncRNA levels frequently alter according to the onset and progression of cancer. Exosomal lncRNAs can therefore be employed as biomarkers for the diagnosis and prognosis of cancer. Exosomal lncRNAs can also monitor the patient's response to chemotherapy while also serving as potential targets for cancer treatment. Here, we discuss the role of exosomal lncRNAs in the biology and possible future treatment of GI cancer.

Circulating messenger RNA variants as a potential biomarker for surveillance of hepatocellular carcinoma

Background and rationale

Liver derived messenger ribonucleic acid (mRNA) transcripts were reported to be elevated in the circulation of hepatocellular carcinoma (HCC) patients. We now report the detection of high-risk mRNA variants exclusively in the circulation of HCC patients. Numerous genomic alleles such as single nucleotide polymorphisms (SNPs), nucleotide insertions and deletions (called Indels), splicing variants in many genes, have been associated with elevated risk of cancer. Our findings potentially offer a novel non-invasive platform for HCC surveillance and early detection.

Approach

RNAseq analysis was carried out in the plasma of 14 individuals with a diagnosis of HCC, 8 with LC and no HCC, and 6 with no liver disease diagnosis. RNA from 6 matching tumors and 5 circulating extracellular vesicle (EV) samples from 14 of those with HCC was also analyzed. Specimens from two cholangiocarcinoma (CCA) patients were also included in our study. HCC specific SNPs and Indels referred as "variants" were identified using GATK HaplotypeCaller and annotated by SnpEff to filter out high risk variants.

Results

The variant calling on all RNA samples enabled the detection of 5.2 million SNPs, 0.91 million insertions and 0.81 million deletions. RNAseq analyses in tumors, normal liver tissue, plasma, and plasma derived EVs led to the detection of 5480 high-risk tumor specific mRNA variants in the circulation of HCC patients. These variants are concurrently detected in tumors and plasma samples or tumors and EVs from HCC patients, but none of these were detected in normal liver, plasma of LC patients or normal healthy individuals. Our results demonstrate selective detection of concordant high-risk HCC-specific mRNA variants in free plasma, plasma derived EVs and tumors of HCC patients. The variants comprise of splicing, frameshift, fusion and single nucleotide alterations and correspond to cancer and tumor metabolism pathways. Detection of these high-risk variants in matching specimens from same subjects with an enrichment in circulating EVs is remarkable. Validation of these HCC selective ctmRNA variants in larger patient cohorts is likely to identify a predictive set of ctmRNA with high diagnostic performance and thus offer a novel non-invasive serology-based biomarker for HCC.

CT Radiomics to Predict Macrotrabecular-Massive Subtype and Immune Status in Hepatocellular Carcinoma

Background Macrotrabecular-massive (MTM) subtype of hepatocellular carcinoma (HCC) is an aggressive variant associated with angiogenesis and immunosuppressive tumor microenvironment, which is expected to be noninvasively identified using radiomics approaches. Purpose To construct a CT radiomics model to predict the MTM subtype and to investigate the underlying immune infiltration patterns. Materials and Methods This study included five retrospective data sets and one prospective data set from three academic medical centers between January 2015 and December 2021. The preoperative liver contrast-enhanced CT studies of 365 adult patients with resected HCC were evaluated. The Third Xiangya Hospital of Central South University provided the training set and internal test set, while Yueyang Central Hospital and Hunan Cancer Hospital provided the external test sets. Radiomic features were extracted and used to develop a radiomics model with machine learning in the training set, and the performance was verified in the two test sets. The outcomes cohort, including 58 adult patients with advanced HCC undergoing transarterial chemoembolization and antiangiogenic therapy, was used to evaluate the predictive value of the radiomics model for progression-free survival (PFS). Bulk RNA sequencing of tumors from 41 patients in The Cancer Genome Atlas (TCGA) and single-cell RNA sequencing from seven prospectively enrolled participants were used to investigate the radiomics-related immune infiltration patterns. Area under the receiver operating characteristics curve of the radiomics model was calculated, and Cox proportional regression was performed to identify predictors of PFS. Results Among 365 patients (mean age, 55 years ± 10 [SD]; 319 men) used for radiomics modeling, 122 (33%) were confirmed to have the MTM subtype. The radiomics model included 11 radiomic features and showed good performance for predicting the MTM subtype, with AUCs of 0.84, 0.80, and 0.74 in the training set, internal test set, and external test set, respectively. A low radiomics model score relative to the median value in the outcomes cohort was independently associated with PFS (hazard ratio, 0.4; 95% CI: 0.2, 0.8; P = .01). The radiomics model was associated with dysregulated humoral immunity involving B-cell infiltration and immunoglobulin synthesis. Conclusion Accurate prediction of the macrotrabecular-massive subtype in patients with hepatocellular carcinoma was achieved using a CT radiomics model, which was also associated with defective humoral immunity. Published under a CC BY 4.0 license. Supplemental material is available for this article. See also the editorial by Yoon and Kim in this issue.

Chromosomal instability-associated MAT1 lncRNA insulates MLL1-guided histone methylation and accelerates tumorigenesis

Acquired chromosomal instability, especially copy number variations (CNVs), has been considered an important determinant of cancer progression and clinical survival. However, the functional role of aberrant CNV-induced lncRNAs in tumorigenesis remains unexplored. Here, we identify a CNV-induced MSC-antisense-transcript 1 (MAT1) lncRNA that plays an oncogenic role in promoting tumorigenesis of uveal melanoma in orthotopic and metastatic xenografts. In addition, our data suggest that MAT1 interrupts the interaction between the MLL1 complex and the PCDH20 promoter by forming an RNA-DNA triplex structure, subsequently abolishing H3K4 trimethylation and inactivating transcription of tumor suppressor PCDH20 to accelerate tumorigenesis. Our data show an intriguing insulation pattern of H3K4 histone modification in tumorigenesis mediated by a lncRNA, thereby providing an alternative mechanism for noncoding blockers in gene regulation.

Pathogenesis to management of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common primary liver cancer whose incidence continues to rise in many parts of the world due to a concomitant rise in many associated risk factors, such as alcohol use and obesity. Although early-stage HCC can be potentially curable through liver resection, liver-directed therapies, or transplantation, patients usually present with intermediate to advanced disease, which continues to be associated with a poor prognosis. This is because HCC is a cancer with significant complexities, including substantial clinical, histopathologic, and genomic heterogeneity. However, the scientific community has made a major effort to better characterize HCC in those aspects via utilizing tissue sampling and histological classification, whole genome sequencing, and developing viable animal models. These efforts ultimately aim to develop clinically relevant biomarkers and discover molecular targets for new therapies. For example, until recently, there was only one approved systemic therapy for advanced or metastatic HCC in the form of sorafenib. Through these efforts, several additional targeted therapies have gained approval in the United States, although much progress remains to be desired. This review will focus on the link between characterizing the pathogenesis of HCC with current and future HCC management.

The role of Neanderthal introgression in liver cancer

BACKGROUND

Neanderthal introgressed DNA has been linked to different normal and disease traits including immunity and metabolism-two important functions that are altered in liver cancer. However, there is limited understanding of the relationship between Neanderthal introgression and liver cancer risk. The aim of this study was to investigate the relationship between Neanderthal introgression and liver cancer risk.

METHODS

Using germline and somatic DNA and tumor RNA from liver cancer patients from The Cancer Genome Atlas, along with ancestry-match germline DNA from unaffected individuals from the 1000 Genomes Resource, and allele specific expression data from normal liver tissue from The Genotype-Tissue Expression project we investigated whether Neanderthal introgression impacts cancer etiology. Using a previously generated set of Neanderthal alleles, we identified Neanderthal introgressed haplotypes. We then tested whether somatic mutations are enriched or depleted on Neanderthal introgressed haplotypes compared to modern haplotypes. We also computationally assessed whether somatic mutations have a functional effect or show evidence of regulating expression of Neanderthal haplotypes. Finally, we compared patterns of Neanderthal introgression in liver cancer patients and the general population.

RESULTS

We find Neanderthal introgressed haplotypes exhibit an excess of somatic mutations compared to modern haplotypes. Variant Effect Predictor analysis revealed that most of the somatic mutations on these Neanderthal introgressed haplotypes are not functional. We did observe expression differences of Neanderthal alleles between tumor and normal for four genes that also showed a pattern of enrichment of somatic mutations on Neanderthal haplotypes. However, gene expression was similar between liver cancer patients with modern ancestry and liver cancer patients with Neanderthal ancestry at these genes. Provocatively, when analyzing all genes, we find evidence of Neanderthal introgression regulating expression in tumor from liver cancer patients in two genes, ARK1C4 and OAS1. Finally, we find that most genes do not show a difference in the proportion of Neanderthal introgression between liver cancer patients and the general population.

CONCLUSION

Our results suggest that Neanderthal introgression provides opportunity for somatic mutations to accumulate, and that some Neanderthal introgression may impact liver cancer risk.

Distinct binding pattern of EZH2 and JARID2 on RNAs and DNAs in hepatocellular carcinoma development

Hepatocellular carcinoma (HCC) is one of the most malignant cancers worldwide, with high mortality. However, the molecular regulatory mechanisms of liver cancer, especially transcriptional and post-transcriptional mechanisms, should be further studied. Here we used chromatin and cross-linking immunoprecipitation with high throughput sequencing methods (ChIP-seq and CLIP-seq) to capture the global binding profiles on RNAs and DNAs of Enhancer of zeste homolog 2 (EZH2) and its partner Jumonji And AT-Rich Interaction Domain Containing 2 (JARID2) in liver carcinoma cell lines (HepG2) and normal liver cell line (THLE-2), respectively. We also integrated HCC transcriptome data from the TCGA to analyze the expression pattern of bound genes. We found that EZH2 and JARID2 both showed distinct binding profiles between HepG2 and THLE-2 cells. By binding to the primary RNAs, bound transcripts of EZH2 and JARID2 in HepG2 showed significantly increased transcriptional levels in HCC patients. By performing gene set enrichment analysis (GSEA), the bound transcripts were also highly related to HCC development. We also found EZH2 and JARID2 could specifically bind to several long noncoding RNAs (lncRNAs), including H19. By exploring the DNA binding profile, we detected a dramatically repressed DNA binding ability of EZH2 in HepG2 cells. We also found that the EZH2-bound genes showed slightly increased transcriptional levels in HepG2 cells. Integrating analysis of the RNA and DNA binding profiles suggests EZH2 and JARID2 shift their binding ability from DNA to RNA in HepG2 cells to promote cancer development in HCC. Our study provided a comprehensive and distinct binding profile on RNAs and DNAs of EZH2 and JARID2 in liver cancer cell lines, suggesting their potential novel functional manners to promote HCC development.

TP53-related signature for predicting prognosis and tumor microenvironment characteristics in bladder cancer: A multi-omics study

Background: The tumor suppressor gene TP53 is frequently mutated or inactivated in bladder cancer (BLCA), which is implicated in the pathogenesis of tumor. However, the cellular mechanisms of TP53 mutations are complicated, yet well-defined, but their clinical prognostic value in the management of BLCA remains controversial. This study aimed to explore the role of TP53 mutation in regulating the tumor microenvironment (TME), elucidate the effects of TP53 activity on BLCA prognosis and immunotherapy response. Methods: A TP53-related signature based on TP53-induced and TP53-repressed genes was used to construct a TP53 activity-related score and classifier. The abundance of different immune cell types was determined using CIBERSORT to estimate immune cell infiltration. Moreover, the heterogeneity of the tumor immune microenvironment between the high and low TP53 score groups was further evaluated using single-cell mass cytometry (CyTOF) and imaging mass cytometry (IMC). Moreover, pathway enrichment analysis was performed to explore the differential biological functions between tumor epithelial cells with high and low TP53 activity scores. Finally, the receptor-ligand interactions between immune cells and tumor epithelial cells harboring distinct TP53 activity were analyzed by single-cell RNA-sequencing. Results: The TP53 activity-related gene signature differentiated well between TP53 functional retention and inactivation in BLCA. BLCA patients with low TP53 scores had worse survival prognosis, more TP53 mutations, higher grade, and stronger lymph node metastasis than those with high TP53 scores. Additionally, CyTOF and IMC analyses revealed that BLCA patients with low TP53 scores exhibited a potent immunosuppressive TME. Consistently, single-cell sequencing results showed that tumor epithelial cells with low TP53 scores were significantly associated with high cell proliferation and stemness abilities and strongly interacted with immunosuppressive receptor-ligand pairs. Conclusion: BLCA patients with low TP53 scores have a worse prognosis and a more immunosuppressive TME. This TP53 activity-related signature can serve as a potential prognostic signature for predicting the immune response, which may facilitate the development of new strategies for immunotherapy in BLCA.

A population-based study of precision health assessments using multi-omics network-derived biological functional modules

Recent technological advances in multi-omics and bioinformatics provide an opportunity to develop precision health assessments, which require big data and relevant bioinformatic methods. Here we collect multi-omics data from 4,277 individuals. We calculate the correlations between pairwise features from cross-sectional data and then generate 11 biological functional modules (BFMs) in males and 12 BFMs in females using a community detection algorithm. Using the features in the BFM associated with cardiometabolic health, carotid plaques can be predicted accurately in an independent dataset. We developed a model by comparing individual data with the health baseline in BFMs to assess health status (BFM-ash). Then we apply the model to chronic patients and modify the BFM-ash model to assess the effects of consuming grape seed extract as a dietary supplement. Finally, anomalous BFMs are identified for each subject. Our BFMs and BFM-ash model have huge prospects for application in precision health assessment.

Role of the Hippo pathway in liver regeneration and repair: recent advances

Although the signaling pathways involved in normal liver regeneration have been well characterized, less has been done for livers affected by chronic tissue damage. These "abnormal livers" have an impaired regenerative response that leads to liver repair and fibrosis. The tumor suppressor Hippo pathway plays a key role in liver regeneration and repair. On this basis, this review discusses recent studies focusing on the involvement of the Hippo signaling pathway during "normal healthy liver regeneration" (i.e., in a normal liver after 2/3 partial hepatectomy) and "abnormal liver regeneration" (i.e., in a liver damaged by chronic disease). This could be an important question to address with respect to new therapies aimed at improving impaired liver regenerative responses. The studies reported here have shown that activation of the Hippo coactivators YAP/TAZ during normal liver regeneration promotes the formation of a new bile duct network through direct BEC proliferation or/and hepatocyte dedifferentiation to HPCs which can trans-differentiate to BECs. Moreover, YAP/TAZ signaling interaction with other signaling pathways mediates the recruitment and activation of Kupffer cells, which release mitogenic cytokines for parenchymal and/or non-parenchymal cells and engage in phagocytosis of cellular debris. In addition, YAP-mediated activation of stellate cells (HSCs) promotes liver regeneration through the synthesis of extracellular matrix. However, in chronically diseased livers, where the predetermined threshold for proper liver regeneration is exceeded, YAP/TAZ activation results in a reparative process characterized by liver fibrosis. In this condition, YAP/TAZ activation in parenchymal and non-parenchymal cells results in (i) differentiation of quiescent HSCs into myofibroblastic HSCs; (ii) recruitment of macrophages releasing inflammatory cytokines; (iii) polarization of macrophages toward the M2 phenotype. Since accumulation of damaged hepatocytes in chronic liver injury represent a significant risk factor for the development of hepatocarcinoma, this review also discussed the involvement of the Hippo pathway in the clearance of damaged cells.

An integrated analysis of the cancer genome atlas data discovers a hierarchical association structure across thirty three cancer types

Cancer cells harbor molecular alterations at all levels of information processing. Genomic/epigenomic and transcriptomic alterations are inter-related between genes, within and across cancer types and may affect clinical phenotypes. Despite the abundant prior studies of integrating cancer multi-omics data, none of them organizes these associations in a hierarchical structure and validates the discoveries in extensive external data. We infer this Integrated Hierarchical Association Structure (IHAS) from the complete data of The Cancer Genome Atlas (TCGA) and compile a compendium of cancer multi-omics associations. Intriguingly, diverse alterations on genomes/epigenomes from multiple cancer types impact transcriptions of 18 Gene Groups. Half of them are further reduced to three Meta Gene Groups enriched with (1) immune and inflammatory responses, (2) embryonic development and neurogenesis, (3) cell cycle process and DNA repair. Over 80% of the clinical/molecular phenotypes reported in TCGA are aligned with the combinatorial expressions of Meta Gene Groups, Gene Groups, and other IHAS subunits. Furthermore, IHAS derived from TCGA is validated in more than 300 external datasets including multi-omics measurements and cellular responses upon drug treatments and gene perturbations in tumors, cancer cell lines, and normal tissues. To sum up, IHAS stratifies patients in terms of molecular signatures of its subunits, selects targeted genes or drugs for precision cancer therapy, and demonstrates that associations between survival times and transcriptional biomarkers may vary with cancer types. These rich information is critical for diagnosis and treatments of cancers.

3D-Epigenomic Regulation of Gene Transcription in Hepatocellular Carcinoma

The fundamental cause of transcription dysregulation in hepatocellular carcinoma (HCC) remains elusive. To investigate the underlying mechanisms, comprehensive 3D-epigenomic analyses are performed in cellular models of THLE2 (a normal hepatocytes cell line) and HepG2 (a hepatocellular carcinoma cell line) using integrative approaches for chromatin topology, genomic and epigenomic variation, and transcriptional output. Comparing the 3D-epigenomes in THLE2 and HepG2 reveal that most HCC-associated genes are organized in complex chromatin interactions mediated by RNA polymerase II (RNAPII). Incorporation of genome-wide association studies (GWAS) data enables the identification of non-coding genetic variants that are enriched in distal enhancers connecting to the promoters of HCC-associated genes via long-range chromatin interactions, highlighting their functional roles. Interestingly, CTCF binding and looping proximal to HCC-associated genes appear to form chromatin architectures that overarch RNAPII-mediated chromatin interactions. It is further demonstrated that epigenetic variants by DNA hypomethylation at a subset of CTCF motifs proximal to HCC-associated genes can modify chromatin topological configuration, which in turn alter RNAPII-mediated chromatin interactions and lead to dysregulation of transcription. Together, the 3D-epigenomic analyses provide novel insights of multifaceted interplays involving genetics, epigenetics, and chromatin topology in HCC cells.

Persistent epigenetic alterations in transcription factors after a sustained virological response in hepatocellular carcinoma

Background and Aim

The risk of hepatocellular carcinoma (HCC) persists in a condition of sustained virologic response (SVR) after hepatitis C virus (HCV) eradication. Comprehensive molecular analyses were performed to test the hypothesis that epigenetic abnormalities present after an SVR play a role in hepatocarcinogenesis.

Methods

Whole-genome methylome and RNA sequencing were performed on HCV, SVR, and healthy liver tissue. Integrated analysis of the sequencing data focused on expression changes in transcription factors and their target genes, commonly found in HCV and SVR. Identified expression changes were validated in demethylated cultured HCC cell lines and an independent validation cohort.

Results

The coincidence rates of the differentially methylated regions between the HCV and SVR groups were 91% in the hypomethylated and 71% in the hypermethylated regions in tumorous tissues, and 37% in the hypomethylated and 36% in the hypermethylated regions in non-tumorous tissues. These results indicate that many epigenomic abnormalities persist even after an SVR was achieved. Integrated analysis identified 61 transcription factors and 379 other genes that had methylation abnormalities and gene expression changes in both groups. Validation cohort specified gene expression changes for 14 genes, and gene ontology pathway analysis revealed apoptotic signaling and inflammatory response were associated with these genes.

Conclusion

This study demonstrates that DNA methylation abnormalities, retained after HCV eradication, affect the expression of transcription factors and their target genes. These findings suggest that DNA methylation in SVR patients may be functionally important in carcinogenesis, and could serve as biomarkers to predict HCC occurrence.